Ligand-biased ensemble receptor docking (LigBEnD): a hybrid ligand/receptor structure-based approach

Area of Science:

• Computational chemistry
• Structural biology
• Drug discovery

Background:

• Ensemble docking uses multiple protein conformations for accurate ligand binding prediction.
• Selecting appropriate protein conformations is crucial but challenging, often leading to false positives.

Purpose of the Study:

• To develop an improved ligand-biased ensemble receptor docking method.
• To create a composite scoring function integrating ligand-based and receptor-based approaches.

Main Methods:

• Developed a ligand-biased ensemble docking strategy.
• Integrated ligand-based atomic property field (APF) method with receptor structure-based docking.
• Utilized a composite scoring function for enhanced accuracy.

Main Results:

• Successfully docked 30 out of 36 ligands in the D3R docking challenge.
• Identified six mis-docked ligands where receptor conformations differed significantly from experimental data.
• Demonstrated the need for sampling beyond experimentally available protein conformations.

Conclusions:

• The developed ligand-biased ensemble docking method enhances ligand pose prediction accuracy.
• The method effectively identifies challenging cases requiring extended receptor conformational sampling.
• This approach advances computational drug discovery by improving docking reliability.